Closed getterupper closed 6 months ago
Did you followed the installation instruction and install the latest pytorch?
Did you followed the installation instruction and install the latest pytorch?
Yes, the version is:
torch 2.2.1+cu118
torchaudio 2.2.1
torchvision 0.17.1
How about mmdetection,mmdetection3d,mmsegmentation,mmengine and mmcv. Are those packages the latest one?
How about mmdetection,mmdetection3d,mmsegmentation,mmengine and mmcv. Are those packages the latest one?
Yes.
Package Version
------------------------- -----------
absl-py 2.1.0
addict 2.4.0
aliyun-python-sdk-core 2.14.0
aliyun-python-sdk-kms 2.16.2
asttokens 2.4.1
attrs 23.2.0
black 24.2.0
blinker 1.7.0
cachetools 5.3.3
certifi 2024.2.2
cffi 1.16.0
charset-normalizer 2.0.4
click 8.1.7
colorama 0.4.6
comm 0.2.1
ConfigArgParse 1.7
contourpy 1.2.0
crcmod 1.7
cryptography 42.0.5
cycler 0.12.1
dash 2.15.0
dash-core-components 2.0.0
dash-html-components 2.0.0
dash-table 5.0.0
decorator 5.1.1
descartes 1.1.0
exceptiongroup 1.2.0
executing 2.0.1
fastjsonschema 2.19.1
filelock 3.13.1
fire 0.5.0
flake8 7.0.0
Flask 3.0.2
focal-loss-torch 0.1.2
fonttools 4.49.0
fsspec 2024.2.0
grpcio 1.62.0
huggingface-hub 0.21.3
idna 3.4
imageio 2.34.0
importlib-metadata 7.0.1
importlib_resources 6.1.2
iniconfig 2.0.0
ipython 8.18.1
ipywidgets 8.1.2
itsdangerous 2.1.2
jedi 0.19.1
Jinja2 3.1.3
jmespath 0.10.0
joblib 1.3.2
jsonschema 4.21.1
jsonschema-specifications 2023.12.1
jupyter_core 5.7.1
jupyterlab_widgets 3.0.10
kiwisolver 1.4.5
lazy_loader 0.3
llvmlite 0.42.0
lyft-dataset-sdk 0.0.8
Markdown 3.5.2
markdown-it-py 3.0.0
MarkupSafe 2.1.3
matplotlib 3.5.3
matplotlib-inline 0.1.6
mccabe 0.7.0
mdurl 0.1.2
mkl-fft 1.3.8
mkl-random 1.2.4
mkl-service 2.4.0
mmcv 2.1.0
mmdet 3.2.0
mmdet3d 1.4.0
mmengine 0.10.3
mmsegmentation 1.2.2
model-index 0.1.11
mpmath 1.3.0
mypy-extensions 1.0.0
nbformat 5.9.2
nest-asyncio 1.6.0
networkx 3.1
numba 0.59.0
numpy 1.26.4
nuscenes-devkit 1.1.11
nvidia-cublas-cu11 11.11.3.6
nvidia-cuda-cupti-cu11 11.8.87
nvidia-cuda-nvrtc-cu11 11.8.89
nvidia-cuda-runtime-cu11 11.8.89
nvidia-cudnn-cu11 8.7.0.84
nvidia-cufft-cu11 10.9.0.58
nvidia-curand-cu11 10.3.0.86
nvidia-cusolver-cu11 11.4.1.48
nvidia-cusparse-cu11 11.7.5.86
nvidia-nccl-cu11 2.19.3
nvidia-nvtx-cu11 11.8.86
open3d 0.18.0
opencv-python 4.9.0.80
opendatalab 0.0.10
openmim 0.3.9
openxlab 0.0.34
ordered-set 4.1.0
oss2 2.17.0
packaging 23.2
pandas 2.2.1
parso 0.8.3
pathspec 0.12.1
pexpect 4.9.0
pillow 10.2.0
pip 24.0
platformdirs 4.2.0
plotly 5.19.0
pluggy 1.4.0
plyfile 1.0.3
prettytable 3.10.0
prompt-toolkit 3.0.43
protobuf 4.25.3
ptyprocess 0.7.0
pure-eval 0.2.2
pycocotools 2.0.7
pycodestyle 2.11.1
pycparser 2.21
pycryptodome 3.20.0
pyflakes 3.2.0
Pygments 2.17.2
pyparsing 3.1.1
pyquaternion 0.9.9
pytest 8.0.2
python-dateutil 2.8.2
pytorch-loss 0.0.0
pytz 2023.4
PyYAML 6.0.1
referencing 0.33.0
requests 2.28.2
retrying 1.3.4
rich 13.4.2
rpds-py 0.18.0
safetensors 0.4.2
scikit-image 0.22.0
scikit-learn 1.4.1.post1
scipy 1.12.0
setuptools 60.2.0
Shapely 1.8.5.post1
six 1.16.0
stack-data 0.6.3
sympy 1.12
tabulate 0.9.0
tenacity 8.2.3
tensorboard 2.16.2
tensorboard-data-server 0.7.2
termcolor 2.4.0
terminaltables 3.1.10
threadpoolctl 3.3.0
tifffile 2024.2.12
timm 0.9.16
tomli 2.0.1
torch 2.2.1+cu118
torchaudio 2.2.1
torchvision 0.17.1
tqdm 4.65.2
traitlets 5.14.1
trimesh 4.1.6
triton 2.2.0
typing_extensions 4.9.0
tzdata 2024.1
urllib3 1.26.18
wcwidth 0.2.13
Werkzeug 3.0.1
wheel 0.42.0
widgetsnbextension 4.0.10
yapf 0.40.2
zipp 3.17.0
Did you use the test command in my instruction to evaluate the model? I have never encountered this issue before.
Did you use the test command in my instruction to evaluate the model? I have never encountered this issue before.
I used bash tools/dist_test.sh configs/InverseMatrixVT3D_200_200_16.py ckpt/InverseMatrixVT3D_200.pth 8
, still encountered the problem.
Please try set enable_fix=False in the config file and run evaluation again.
Please try set enable_fix=False in the config file and run evaluation again.
Perhaps it's due to the cuda version. Which version did you use?
I used pytorch 2.2 with cuda11.8. Please make sure the Pytorch version and Cuda version are aligned. I recommend using the latest Pytorch and Cuda versions.
I used pytorch 2.2 with cuda11.8. Please make sure the Pytorch version and Cuda version are aligned. I recommend using the latest Pytorch and Cuda versions.
Solved it. Many thanks!
Hi, when testing InverseMatrixVT3D for $200\times200\times16$ resolution, I encounter such a problem: RuntimeError: Unknown layout
I can't find a way to fix this, Thanks